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Record W2902621398 · doi:10.1080/02773813.2018.1494745

Effect of Wood Welding Process on Chemical Constituents of Australian Eucalyptus

2018· article· en· W2902621398 on OpenAlexaff
Benoît Belleville, Georges Koumba-Yoya, Tatjana Stevanović

Bibliographic record

VenueJournal of Wood Chemistry and Technology · 2018
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversité Laval
FundersUniversity of Melbourne
KeywordsChemistryEucalyptusPulp and paper industryProcess (computing)WeldingHardwoodBotanyMetallurgy

Abstract

fetched live from OpenAlex

Thermochemical changes occurring during wood welding were investigated in Eucalyptus saligna and Eucalyptus pilularis. Unwelded reference wood and material from welded interface were compared via Py-GC/MS, thermogravimetric analyses, X-ray photoelectron spectroscopy, and attenuated total reflection Fourier transform infrared spectroscopy to explain differences in mechanical properties of welded wood between species. It appeared that the species originally containing more condensed substructures also provided stronger joints. The condensation index after welding allowed validating that the adhesive properties of lignin are more accessible in such species. The presence of more carbonyl functions, attributed to carbohydrate solicitation during welding process, potentially made lignin less accessible. Changes following welding were evidenced by the contribution of extractive compounds, fatty acid chains, and terpenoids, possibly reacting with hydroxyl groups and leading to adhesive properties by chemical linkage through new covalent bonds formation. Results corroborate the better mechanical properties of E. saligna, providing stronger joints possibly due to more accessible adhesive properties by esterification between lignin and fatty acid.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.229
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2018
Admission routes1
Has abstractyes

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